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Harmonized quality assurance/quality control provisions to assess completeness and robustness of MS1 data preprocessing for LC-HRMS-based suspect screening and non-targeted analysis.

Authors :
Lennon, Sarah
Chaker, Jade
Price, Elliott J.
Hollender, Juliane
Huber, Carolin
Schulze, Tobias
Ahrens, Lutz
Béen, Frederic
Creusot, Nicolas
Debrauwer, Laurent
Dervilly, Gaud
Gabriel, Catherine
Guérin, Thierry
Habchi, Baninia
Jamin, Emilien L.
Klánová, Jana
Kosjek, Tina
Le Bizec, Bruno
Meijer, Jeroen
Mol, Hans
Source :
Trends in Analytical Chemistry: TRAC. May2024, Vol. 174, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

Non-targeted and suspect screening analysis using liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) holds great promise to comprehensively characterize complex chemical mixtures. Data preprocessing is a crucial part of the process, however, some limitations are observed: (i) peak-picking and feature extraction might be incomplete, especially for low abundant compounds, and (ii) limited reproducibility has been observed between laboratories and software for detected features and their relative quantification. We first conducted a critical review of existing solutions that could improve the reproducibility of preprocessing for LC-HRMS. Solutions include providing repositories and reporting guidelines, open and modular processing workflows, public benchmark datasets, tools to optimize the data preprocessing and to filter out false positive detections. We then propose harmonized quality assurance/quality control guidelines that would allow to assess the sensitivity of feature detection, reproducibility, integration accuracy, precision, accuracy, and consistency of data preprocessing for human biomonitoring, food and environmental communities. • Preprocessing of raw data from SS and NTA by (LC-HRMS) is affected by reproducibility and incomplete peak peaking. • Optimization tools and guidelines were developed to improve SSA/NTA LC-HRMS data preprocessing. • QA/QC provisions for SSA/NTS LC-HRMS data preprocessing are proposed to assess performance of preprocessing. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01659936
Volume :
174
Database :
Academic Search Index
Journal :
Trends in Analytical Chemistry: TRAC
Publication Type :
Academic Journal
Accession number :
177086068
Full Text :
https://doi.org/10.1016/j.trac.2024.117674